Journal Articles European Journal of Operational Research Year : 2023

Dendrograms, Minimum Spanning Trees and Feature Selection

Abstract

Feature selection is a fundamental process to avoid over tting and to reduce the size of databases without signi cant loss of information that applies to hierarchical clustering. Dendrograms are graphical representations of hierarchical clustering algorithms that for single linkage clustering can be interpreted as minimum spanning trees in the complete network de ned by the database. In this work, we introduce the problem that determines jointly a set of features and a dendrogram, according to the single linkage method. We propose di erent formulations that include the minimum spanning tree problem constraints as well as the feature selection constraints. Di erent bounds on the objective function are studied. For one of the models, several families of valid inequalities are proposed and the problem of separating them is studied. For another formulation, a decomposition algorithm is designed. In an extensive computational study, the e ectiveness of the di erent models is discussed, the model with valid inequalities is compared with the decomposition algorithm. The computational results also illustrate that the integration of feature selection to the optimization model allows to keep a satisfactory percentage of information.
Fichier principal
Vignette du fichier
Dendrograms__Minimum_Spanning_Trees_and_Feature_Selection.pdf (530) Télécharger le fichier
Origin Files produced by the author(s)

Dates and versions

hal-03727566 , version 1 (19-07-2022)

Identifiers

Cite

Martine Labbé, Mercedes Landete, Marina Leal. Dendrograms, Minimum Spanning Trees and Feature Selection. European Journal of Operational Research, 2023, 308 (2), pp.555-567. ⟨10.1016/j.ejor.2022.11.031⟩. ⟨hal-03727566⟩
101 View
141 Download

Altmetric

Share

More